An Integrated Systems Approach to Infer Protein Networks Associated with Chronic Obstructive Pulmonary Disease

Abstract

Chronic obstructive pulmonary disease (COPD) is a widespread and fatal respiratory condition that affects millions globally. Despite its prevalence, effective interventions to halt or reverse disease progression remain limited due to an incomplete characterization of COPD’s underlying mechanisms. Recent strides in understanding the pathobiology of COPD highlight its heterogeneous nature, encompassing diverse respiratory and systemic manifestations that likely stem from pathological changes across multiple biological pathways.

To navigate the intricate landscape of COPD pathogenesis, this thesis employs a network-based approach utilizing data-driven modeling techniques. These methodologies can help unravel complex pathological networks by facilitating the modeling of interactions among multiple biological factors, thus providing novel insights into the systems-level mechanisms underlying disease states. Furthermore, data-driven techniques permit the integration of data from diverse tissue compartments, offering a more holistic depiction of disease pathology.

In this thesis, we applied data-driven techniques to high-throughput protein measurements from human blood and lung samples. Overall, this approach revealed proteomic signatures that differentiate distinct COPD subpopulations and offered novel insights into disease progression and its underlying molecular drivers. Our findings specifically introduce new perspectives into mechanisms governing rapid spirometric decline, age-dependent emphysema development, and immune cell communication networks within COPD. Mechanistically, our investigations suggest a critical role for early modifications in the complement cascade in lung function decline, highlight a unique contribution of inflammatory and apoptotic pathways in early emphysema development, and elucidate deficiencies in the adaptive immune responses of individuals with COPD.

In summary, this work provides novel insights into potential mechanisms driving COPD pathogenesis and progression, while also establishing a framework for exploring other heterogeneous diseases. Our findings underscore the importance of adopting a network-level approach in studying COPD and of integrating data from diverse sources to uncover new molecular insights. Furthermore, this thesis highlights the difficulties of studying complex diseases, and as a result, the methods and insights presented here carry broader significance for investigating other progressive and heterogeneous conditions extending beyond COPD.